Database Paper Browser

Back to papers

Anonymizing Bipartite Graph Data using Safe Groupings

Summary: Introduces (k, l)-groupings for bipartite graphs that preserve the graph structure perfectly while anonymizing the mapping from entities to graph nodes. Proposes safe groupings with provable attack resistance, algorithms to find them, and real-data experiments showing strong privacy-utility tradeoffs. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
9718
Venue
VLDB
Year
2008
Pagerank
8.2409647e-05
Overall Rank
2,718 | 81.10%
DOI
-

Incoming Non-self Citations Over Time

Authors

Incoming Citations (Sorted by Pagerank)

Showing 14 of 14 citing papers.

Previous Page 1 / 1 Next

Outgoing Citations (Sorted by Pagerank)

Showing 2 of 2 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank Cited Paper Year Venue Pagerank
654 Anatomy: Simple and Effective Privacy Preservation 2006 VLDB 0.00018613167
1,382 Minimality Attack in Privacy Preserving Data Publishing 2007 VLDB 0.00012281313
Previous Page 1 / 1 Next

Semantically Similar Papers